In general, products of the chemical industry fall into one of two types—formulaic chemicals and performance chemicals. Formulaic chemicals are defined by their composition. If they are sold in different grades, the grades are distinguished by the concentration of impurities. Examples include ammonia, benzene, carbon tetrachloride, diethyl ether, formaldehyde, soda ash, and calcium oxide. Performance chemicals, which include polymers, dyes, pigments, and fragrances, are valued because of what they do, not what their composition is. Important types of performance chemicals include fine particle products such as carbon black, silica, titania, tantalum, calcium carbonate which are used in applications including reinforcement, rheology, color, and conductivity.
Fine particles are used to enhance such properties of compound materials as rheology, flow, strength, color, etc. The ability of the fine particle product to achieve the desired level of performance depends upon particle characteristics. In order to differentiate classes of performance, types or grades are commonly defined. These definitions include the designation of certain particle properties and the assignment of typical or target values for those properties. Prior to the present invention, the particle properties have been related to morphology; e.g. particle size, particle size distribution, particle shape or structure, and the like.
In order to insure consistency, specifications are set for fine particle products. Typically these specifications will include one or more measures of morphology and may further include one or more measures of chemical constituents. Common measures of morphology are particle size, surface area, structure, porosity, aggregate size, and aggregate shape. Common measures of chemistry include bulk and surface composition as well as analyses of extractable species. Measurements of variability of these properties can be made either during manufacturing to insure the process remains in control (often referred to as quality control, or QC) or on the product prior to shipment (often referred to as quality assurance, or QA).
For example, carbon black is typically sold with at least one morphological specification, which may be surface area, particle size, structure, and porosity. Performance tests, such as, for example, bound rubber or compound moisture absorption (CMA) tests may also be run, depending on the intended use for the carbon black. However, these are not typically included on a product specification sheet.
Despite these quality control and quality assurance (QC/QA) efforts, it is not unusual for a customer to complain that a batch of product received did not perform as expected, despite being “within spec”. For example, variations in the rate of rubber cure, the appearance of white haze on molded rubber parts, low thixotropy in adhesives, and variations in plastic compounding times have all been traced back to lot-to-lot variations of carbon blacks even when each lot was within specification. This often results in the producer undertaking a thorough and costly study of the process and product and trying to make adjustments so that the product once again performs as expected. Since there can be such variation in product performance for particulate materials, it is difficult for a customer or particulate manufacturer to select the best particulate for the composition. How can the product performance be at its best, when the particulate material and its interactions in the composition are not fully appreciated or understood? The present invention permits one to achieve improved performance by providing a better appreciation, a better understanding, and a better selection of particulate materials.
Determining why a product did not perform as expected is inefficient and often both time consuming and expensive. It involves evaluation to assess why a problem has occurred rather than avoiding the problem in the first place. Many times, the producer will adjust manufacturing steps, not understanding the result but only in an attempt to change the product somehow to see a product difference. At times, this amounts to guess work.
Since performance of the particulate materials in a composition can be a problem as explained above, there is a need to develop means to select particulate material to optimize the performance in a matrix or composition to avoid or minimize the above-described problems. Also, there is a need to develop an improved system for allowing the proper or optimal selection of particulate materials for a matrix or composition, for instance, that will permit an improved or optimized performance in an application.